Anti-islanding Detection Research Articles

Anti-islanding image detection and optimization of distributed power supply using neural network architecture search

Anti-islanding detection (AILD) for distributed power sources plays an important role on the stable operation of power grid systems and the safety of electrical systems. In order to improve the detection accuracy, we propose neural network architecture search (NAS) based approach for anti-islanding image detection and optimization of distributed power sources. It combines the fast region-based convolutional neural network (Faster-R-CNN) with the differentiable architecture search (Darts), utilizing electrical signal image data acquired from cameras or photovoltaic (PV) inverters, thereby enhancing the accuracy and efficiency of detection. We conduct a comparative analysis of two methods for obtaining distributed power supply (DPS) anti-islanding image data: camera-based acquisition and PV inverter-based acquisition. Our observation reveals that the image data acquired through cameras is more conducive for the learning process of DCNN. The proposed algorithm was compared with other convolutional neural network (CNN) models, validating its performance superiority. This provides a novel perspective and methodology for the advancement of AILD for distributed power sources, and enhances the security and stability of DPS.

Investigation of condition monitoring system for grid connected photovoltaic (GCPV) system with power electronics converters using machine learning techniques

Power systems protection has become more vital in recent years to ensure stability, reliability, security, and power quality due to the exponential growth of grid-connected photovoltaic (GCPV) systems. As a result, several nations have set new grid codes for the grid integration of PV plant installations to overcome these concerns. Investigating Fault Ride Through (FRT) capacity is one of the primary criteria for grid codes. For 3-phase GCPV systems, fault detection and classification approaches are proposed in this study. Firstly, different faults that occurred in the GCPV system are categorized and compared, with the critical and analytical evaluation of grid codes, particularly FRT requirements such as Low Voltage Ride Through (LVRT) and High Voltage Ride Through (HVRT) for different nations. Further, a detailed classification and a comparison of the existing FRT techniques are presented for better control methods based on system complexity, detection accuracy, and other evolutionary criteria. To ensure smooth grid operation, accurate fault detection and condition monitoring of the systems are required. This paper discusses a machine learning (ML) based technique for detecting faults in 3-phase GCPV systems. Multi-peak phenomena caused by FRT capabilities and anti-islanding detection are the main problems experienced while integrating a PV system into the local grid. The fault classification technique is developed using weighted K-nearest neighbor (WKNN) and fine Gaussian support vector machine (FGSVM) based ML approaches utilizing Wavelet Transform. The proposed ML-based findings show that the fault detection algorithm-based classification accuracy has significantly improved.

Comparison of a Novel AFPSO-SFS & PSO-SFS Approaches for Islanding Protection of Inverter-Based DGs

The most significant of the active islanding detection techniques is “Sandia Frequency Shift” (SFS), and this employs frequency drifting to identify extra Nondetection Zone. Inappropriate tuning parameters, such as the acceleration factor and chopping factor, result in frequency drifting, which degrades the quality of the power and causes the continuous power mode to fail. The failure can be overcome by considering optimized parameters to identify the nondetection zone (NDZ) in small DG system (120 kVA) at constant power/current mode. This article discusses, a new Adaptive Fuzzy Particle Swarm Optimization-SFS (AFPSO-SFS) technique is recommended to attain optimal parameters of SFS anti-islanding detection technique for validation of the proposed algorithm Particle Swarm Optimization–SFS (PSO-SFS) is also implemented. Furthermore, the ability of this method is to identify an islanding situation which deteriorates the major scientific issues for small DG system. Thus, the optimized parameter helps to attain an anti-islanding as well as less impact on power quality. Moreover, this article concerns serious issue of the grid interconnected DG model in an islanding condition, when the utility line would be unintentionally isolated. The grid detachment is generally considered as a fault. When an islanding occurs, the DG protection system must be inactive to detect the fault. For the investigation of power mismatches, the output of considered system using the proposed methods is contrast with results obtained from PSO-SFS and conventional SFS. The recommended strategy analyzes islands more effectively and diagnoses nondetection zones more accurately. The recommended method’s reliability is calculated quantitatively and emulated with MATLAB/Simulink.

Anti-islanding detection in grid-connected inverter system using active frequency drift technique with random forest

Anti-islanding detection in grid-connected inverter system using active frequency drift technique with random forest

Research on anti-islanding detection technology strategy

In recent years, the conditions and environment of China's economic development have undergone or are about to undergo many major changes. At the same time, China's electricity consumption ranks the first in the world with a huge volume and a considerable annual net increment. It is necessary to dialectically understand the profound impact of the new normal of economic development on the growth of China's electricity demand. Faced with the ever-increasing power demand, the power industry is still heavy to ensure steady supply, and the proportion of power consumption will also gradually increase. The central position of power in the energy field is gradually promoted, and the power security guarantee has gradually become one of the core elements of the new energy security strategy: in the actual operation of the power grid, there will be some unstable operation, and the local power grid accident can easily expand into a large-scale blackout. This will not only threaten the daily consumption of electricity, but also affect the national economy to a certain extent. The proposed distributed generation system solves this problem, but it also brings new problems. The appearance of island effect brings more harm to power grid operation. Aiming at the harm of island effect, this paper puts forward the detection technology strategy of related island effect.

Review, analysis, and performance evaluation of the most common four active methods for islanding detection in grid-connected photovoltaic systems

• The AFD, SFS, SMS, and SVS active islanding detection methods. • The studied methods provide good detection times within the new grid standards. • The methods have good detection times under different parameters and scenarios. • The active methods are studied and compared for the first time in a detailed study. This paper systematically analyzes the islanding performance under different case studies and scenarios of the most well-known active islanding detection methods (IDMs) for single-phase grid-connected photovoltaic (PV) systems. They are named as follows: Active Frequency Drift (AFD), Sandia Frequency Shift (SFS), Slip Mode frequency Shift (SMS), and Sandia Voltage Shift (SVS) anti-islanding detection strategies. The performance of these four active anti-islanding methods has been examined in detail using Matlab/Simulink. Moreover, the quality factor and non-detection zone (NDZ) influence on islanding detection is also analyzed. According to the new grid codes and standards, the studied active IDMs provide good detection times. Furthermore, the case studies illustrate that these active detection techniques can successfully detect the islanding operation mode under different quality factors, types of loads, solar irradiance changes, and fault-ride through (FRT) operation mode.

Modified Sandia voltage shift anti‐islanding scheme for distributed power generator systems

This study presents an active anti-islanding technique for distributed power generator systems. The proposed scheme is based on the Sandia voltage shift (SVS) technique, which is characterised by a small non-detection zone (NDZ) and by an acceptable solution to the trade-off between the output power quality and the effectiveness of islanding detection. The proposed technique has the advantage to improve the NDZ and to reduce the anti-islanding detection times. This is due to the exponential-product modification made in the positive feedback to inject current, thereby making the response faster than SVS. Additionally, a self-adaptive gain is considered to achieve a low total harmonic distortion at different power levels. Moreover, the proposed scheme has been validated with theoretical and numerical analysis and experimental results. Finally, the behaviour and performance of the proposed technique are compared with other recent techniques.

Effective Utilization of Limited Channel PMUs for Islanding Detection in a Solar PV Integrated Distribution System

The advancements in the field of wind turbine, solar photovoltaic (PV), fuel cell coupled with improved power electronics have increased reliability of renewable energy sources. The environmental benefits of these sources have forced the power industry to switch over for more distributed generations to meet the increasing load demand. Islanding in distribution system occurs when a portion of distribution system gets isolated from the rest of the grid and continues to supply the local load. Practically, all distributed generations (DG) are required to be disconnected immediately after the formation of island. It is done primarily to take care of safety of the operating personnel and to prevent power quality issues. Effective detection of islanding is an important area of concern. Prior to the integration of DG to the main electrical grid, each DG must be equipped with a suitable anti-islanding detection technique. In this paper, phasor measurement unit (PMU)-based islanding detection technique is presented. The requirement of channel limits of PMUs is also incorporated, and significant results of industry and utility have been obtained. The study has been carried out using MATLAB/Simulink (version 2018a) creating several islanding and non-islanding cases in a PV integrated distribution grid.

Improvement of energy harvesting capability in grid-connected photovoltaic micro-inverters

ABSTRACTIn this paper, a multi-stage micro-inverter system depending on a dual neutral point clamped (D-NPC) inverter is developed for low power photovoltaic (PV) applications. The primary objectives of this study are determined as improving the performance of the proposed D-NPC inverter-based micro-inverter and its controller to ensure better system reliability and promote the overall efficiency. In comparison with conventional systems, the designed system provides many advantages: (1) utilization of lower rating switching components, (2) reduced switching frequency and voltage stress, (3) reduced the size of filter components, (4) higher efficiency, and (5) lower total harmonic distortion (THD). The weighted efficiency of the system is remarkably increased by the value of 2.15% compared to the conventional micro-inverter and reached 93.73%. Furthermore, the THD value of the output current is measured below 3% for the proposed system with the small size of passive filtering elements. Further, dynamic grid support and anti-islanding detection capabilities are provided through the utilized controller structure to fulfill grid codes. Consequently, obtained results demonstrate that the improved system can be a considerable candidate for photovoltaic micro-inverter applications in terms of weighted efficiency, output current THD, and reasonable cost.

Review of Local Network Impedance Estimation Techniques

As a result of increasing variability of network impedance, interest in impedance estimation techniques is growing. This review contextualises local impedance estimation techniques by providing a historical prospective on the uses of these techniques, from the early implementations designed to monitor power quality to the latest techniques integrated into converters designed to update the controller with the most recent network information. This is followed by clear and consolidated descriptions, a complete classification and comparison tables of local estimation techniques intended to assist engineers and researchers choose an estimation technique that is suitable to their application. The discussed techniques are then ranked for a range of application priorities such as accuracy, least disruptive to the network, most suitable for wide frequency spectrum estimations and rapidity of estimation. Practical applications of impedance estimation are discussed, such as network characterisation, anti-islanding detection, filter resonance avoidance and controller tuning. To conclude the review, future trends are identified.

Island detection methods and grid current control methods in SPV-based energy systems

ABSTRACT Nowadays, greater penetration of distributed power generation sources (DPGSs), which includes both conventional and renewable energy sources, is taking place, with clear evolution of active grids, i.e. with energy storage systems, there is a possibility to work in an island mode and can be linked to a flexible transmission system, but due to this complexity, the requirements depend on the size and the level of integration. Monitoring of grid is a crucial part, and detection of possible islanding is very important, and in the case of low-power DPGSs like photovoltaic (PV) sources, it is termed as anti-islanding requirement and islanding detection is required in such cases. In future, smart micro grid (SMG) is the scenario i.e. capable of switching automatically to stand-alone operation during grid faults and reconnecting to the grid immediately after the fault is cleared. For this to happen, detection of islanding is important since it is not possible to predict the level of connection and information exchange reliability. Islanding detection is attained with attention towards amplitude and frequency variation of the grid voltages, and the performance of islanding detection relies on reliability, selectivity and minimum perturbation with reference to effects on grid voltage amplitude, and the frequency of the non-detection zone (NDZ) is defined.

On the Conflict between LVRT and Line Protection in LV Distribution Systems with PVs: A Current-Limitation-Based Solution

The upcoming adoption of low-voltage-ride-through requirements in low-voltage distribution systems is expected to raise significant challenges in the operation of grid-tied inverters. Typically, these inverters interconnect photovoltaic units, which are the predominant distributed energy resource in low-voltage distribution networks, under an umbrella of standards and protection schemes. As such, a challenging issue that should be considered in low-voltage distribution network applications, regards the coordination between the line protection scheme (typically consisting of a non-settable fuse) and the low-voltage-ride-through operation of photovoltaic generators. During a fault, the fuse protecting a low-voltage feeder may melt, letting the generator to continue its ride-through operation. Considering that the efficacy/speed of the anti-islanding detection is affected by ride-through requirements, this situation can lead to protracted energization of the isolated feeder after fuse melting (unintentional islanding). To address this issue, this paper proposes a fault-current-limitation based solution, which does not require any modification in the existing protection scheme. The operation principles, design, and implementation of this solution are presented, while, its effectiveness is supported by extensive simulations in a test-case low-voltage distribution system. A discussion on the presented results concludes the paper.

Impedance Measurement and Detection Frequency Bandwidth, a Valid Island Detection Proposal for Voltage Controlled Inverters

Anti-islanding detection methods have been part of a secure operation for distributed energy resource inverters, avoiding the creation of non-intentional energization when the mains are lost. These detection mechanisms were conceived historically for current-controlled inverters. New control possibilities have broken ground, and current- or voltage-controlled inverters are a reality; however, special attention must be paid to detection strategies when applied to the latter ones. This paper addresses two topics: it exposes the lack of effectiveness of those detection algorithms based on the voltage/frequency displacement concept under voltage-controlled inverters and evaluates the applicability limits of the others based on the impedance measurement (IM). The IM is presented as a valid mechanism to achieve the islanding detection, but the exploration of its limits drives the concept of detection frequency bandwidth (DFBW), introduced in this paper. The DFBW is suggested as a practical approach to select the proper injection frequency to measure. Therefore, an improved strategy based on the IM and DFBW is proposed to allow achieving the detection towards (non-)resonant loads considering low computational burden. The results were experimentally validated in a 90-kVA four-wire voltage-controlled inverter, offering detection times of less than 100 ms in any case.

Active Cross-Correlation Anti-Islanding Scheme for PV Module-Integrated Converters in the Prospect of High Penetration Levels and Weak Grid Conditions

This paper introduces a new cross-correlation anti-islanding detection scheme for module-integrated converters (MICs) with pseudo dc-link. The proposed scheme periodically injects a second-order harmonic current component of low magnitude (in open-loop mode) and evaluates grid response by means of correlation. The proposed scheme is highly reliable, providing nondetection-zone free operation, fast detection, and compliance with the relevant power quality and anti-islanding standards. Additionally, it excels in lower computational cost, reduced fault detection zone, and higher output power quality, compared to the referenced anti-islanding schemes that are compatible with MICs. Last but not least, it can be implemented in MIC platforms without requiring an output current sensor, being an easily upgradable solution in software level. A firm theoretical framework that considers both high penetration levels of PV systems and weak grid conditions is also included in this paper. The theoretical framework, as well as the effectiveness of the proposed scheme, is verified through extensive experimental results for various electrical-network parameters and nonlinear loading conditions. Finally, a comprehensive comparison between the proposed method and the most common anti-islanding techniques (compatible with MICs) is performed, leading to some valuable conclusions from MICs perspective.

Simultaneous Implementation of LVRT Capability and Anti-Islanding Detection in Three-Phase Inverters Connected to Low-Voltage Grids

In the future, the provision of ancillary services in low-voltage grids will become more and more important. Low-voltage ride-through capability has been a requirement in medium- and high-voltage grids but will become mandatory even in low-voltage grids. There may be conflicts with existing requirements such as anti-islanding detection. This paper proposes a method that allows for both low-voltage ride-through capability and anti-islanding protection to be implemented simultaneously in three-phase inverters connected to low-voltage grids. This method uses constant voltage and frequency monitoring and reacts according to the relevant specific requirements. With the proposed method, inverters can contribute to system stability without the risk of unintentional islanding operation. The implementation of low-voltage ride-through capability is shown to even facilitate the detection of islanded grids. To prove the merit of this proposal, a model for a three-phase inverter is developed, which incorporates the proposed method and is successfully tested both in simulation and in experiments in the laboratory.

Proposed Sandia frequency shift for anti-islanding detection method based on artificial immune system

Sandia frequency shift (SFS) is one of the active anti-islanding detection methods that depend on frequency drift to detect an islanding condition for inverter-based distributed generation. The non-detection zone (NDZ) of the SFS method depends to a great extent on its parameters. Improper adjusting of these parameters may result in failure of the method. This paper presents a proposed artificial immune system (AIS)-based technique to obtain optimal parameters of SFS anti-islanding detection method. The immune system is highly distributed, highly adaptive, and self-organizing in nature, maintains a memory of past encounters, and has the ability to continually learn about new encounters. The proposed method generates less total harmonic distortion (THD) than the conventional SFS, which results in faster island detection and better non-detection zone. The performance of the proposed method is derived analytically and simulated using Matlab/Simulink. Two case studies are used to verify the proposed method. The first case includes a photovoltaic (PV) connected to grid and the second includes a wind turbine connected to grid. The deduced optimized parameter setting helps to achieve the “non-islanding inverter” as well as least potential adverse impact on power quality.

Impacts of Low-Voltage Distribution Grid Codes on Ancillary Services and Anti-Islanding Detection of Inverter-Based Generation

The capacity to provide ancillary services has become more and more important for generators in the distribution grid. New grid codes have been implemented which regulate inverter behavior regarding different aspects of system safety and stability. This mainly includes the frequency-dependent power reduction or the allocation of reactive power. These standards affect mains monitoring because the power control directly changes penetration after the generator has islanded. In this paper, equations for active and reactive power balance are set up and developed further. Non-Detection Zones for different control methods are shown. These are then described and interpreted in detail to show how different effects that result from grid codes interfere with one another. Frequency-dependent power reduction was found to change the size and shape of the Non-Detection Zones. Reactive power control results in a shift of the Non-Detection Zones. In fact, even the initial operating point before loss of mains has an impact on inverter behavior after islanding. Islanding operating points are sometimes undefined which leads to oscillation. An interpretation of the results and advice for future revisions of grid codes conclude the paper.

Islanding Detection Based on High Frequency Injection for Multi Inverter Microgrid

Islanding detection is one of the indispensable protection detections for grid-connected inverters. The detection of islanding is the key factor that should be considered in the analysis of grid-connection security. The non-detection zone is the performance index of anti-islanding plan. According to the phase feature, quantitative analyses of the non-detection zone of several frequency disturbance schemes are conducted under several different coordinate systems by increasing disturbance, namely injecting third harmonic to the modulating wave that produces inverter drive signal and detects the voltage value and the total harmonic distortion of the power grid. The active current all-disturbance islanding detection scheme has been chosen as the initiative scheme of anti-islanding detection to complete the parameter design and simulation. According to the experimental result, this method is feasible to detect the island of microgrid. In this paper, the simulation model of islanding detection of microgrid is established through MATLAB/SIMULINK, and the simulation analysis of islanding phenomenon after the injection of third harmonic wave is conducted. The simulation result verifies the validity and availability of the islanding detection method.

Investigation of the stability of the anti-islanding detection in multi-DGs system

Investigation of the stability of the anti-islanding detection in multi-DGs system

New Low-Distortion $Q$–$f$ Droop Plus Correlation Anti-Islanding Detection Method for Power Converters in Distributed Generation Systems

A new active Q-f droop anti-islanding (AI) algorithm is proposed. The method is based on frequency and reactive power cross-correlation measures. The proposed control technique is intended to fulfill recent and future grid code requirements. The algorithm looks for a zero nondetection zone, adding low disturbances, working with long frequency excursions and nondependence of the power factor setpoint. The method was verified using a set of simulation models developed in PSCAD environment. The tests show results for several quality factors and different active power levels. In addition, a comparative analysis against other AI methods is presented. Experimental and simulation tests provide further insight on the controllers performance under different working conditions, considering several quality factors and active power levels. Moreover, its performance is assessed comparing the proposed controller behavior against state-of-the-art AI methods.